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authorLars-Dominik Braun <ldb@leibniz-psychology.org>2020-02-04 14:08:37 +0100
committerRicardo Wurmus <rekado@elephly.net>2020-02-22 20:42:12 +0100
commitd228795210de4535d817f8fbc696e82c0800e2f3 (patch)
tree7a87d6c6f4313228616c9ea2275530a535a110db
parent8b217feb3b242484de1917a1c19402281eb95cf7 (diff)
downloadpatches-d228795210de4535d817f8fbc696e82c0800e2f3.tar
patches-d228795210de4535d817f8fbc696e82c0800e2f3.tar.gz
gnu: Add r-stanheaders.
* gnu/packages/cran.scm (r-stanheaders): New variable.
-rw-r--r--gnu/packages/cran.scm36
1 files changed, 36 insertions, 0 deletions
diff --git a/gnu/packages/cran.scm b/gnu/packages/cran.scm
index b69311a39b..1f778d73d1 100644
--- a/gnu/packages/cran.scm
+++ b/gnu/packages/cran.scm
@@ -19766,3 +19766,39 @@ offers additional cost functions, cross validation, and other extensions
beyond traditional structural equation models. It also contains a function to
perform @dfn{exploratory mediation} (XMed).")
(license license:gpl2+)))
+
+(define-public r-stanheaders
+ (package
+ (name "r-stanheaders")
+ (version "2.19.0")
+ (source
+ (origin
+ (method url-fetch)
+ (uri (cran-uri "StanHeaders" version))
+ (sha256
+ (base32
+ "0kyka130sin4nbji7p840394ynhmaynv9jyi94ddbplj83i2nhx3"))))
+ (properties `((upstream-name . "StanHeaders")))
+ (build-system r-build-system)
+ (inputs `(("pandoc" ,ghc-pandoc)))
+ (native-inputs `(("gfortran" ,gfortran)))
+ (home-page "https://mc-stan.org/")
+ (synopsis "C++ header files for Stan")
+ (description
+ "The C++ header files of the Stan project are provided by this package.
+There is a shared object containing part of the @code{CVODES} library, but it
+is not accessible from R. @code{r-stanheaders} is only useful for developers
+who want to utilize the @code{LinkingTo} directive of their package's
+DESCRIPTION file to build on the Stan library without incurring unnecessary
+dependencies.
+
+The Stan project develops a probabilistic programming language that implements
+full or approximate Bayesian statistical inference via Markov Chain Monte
+Carlo or variational methods and implements (optionally penalized) maximum
+likelihood estimation via optimization. The Stan library includes an advanced
+automatic differentiation scheme, templated statistical and linear algebra
+functions that can handle the automatically differentiable scalar types (and
+doubles, ints, etc.), and a parser for the Stan language. The @code{r-rstan}
+package provides user-facing R functions to parse, compile, test, estimate,
+and analyze Stan models.")
+ (license license:bsd-3)))